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Semantic Segmentation On Vaihingen

評価指標

mIoU

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
mIoU
Paper TitleRepository
CMX82.87CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
SegFormer-B075.57SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
SA-Gate81.03Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
HRNet-4876.75Deep High-Resolution Representation Learning for Visual Recognition
SegFormer-B276.69SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
UnetFormer77.24UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
PSPNet76.79Pyramid Scene Parsing Network
LMFNet-2 (82.49LMFNet: An Efficient Multimodal Fusion Approach for Semantic Segmentation in High-Resolution Remote Sensing-
V-FuseNet79.56Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks
SegFormer-B176.92SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
DeepLabV3+72.90Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
HRNet-1875.90Deep High-Resolution Representation Learning for Visual Recognition
FPN74.86Feature Pyramid Networks for Object Detection
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Semantic Segmentation On Vaihingen | SOTA | HyperAI超神経